Known study methods make use of written materials, relying on a user's discipline and drive to keep them working. Conventional review courses provide potential examinees with workbooks, which provide several hundred practice questions that the user can work through, as he/she prefers. At the end of these workbooks appear answers and explanations for the questions.
A major problem with these traditional approaches is that they do not, and cannot, force the user to study in a consistent, systematic and effective way. As a result, the effectiveness of studying changes from one user to another, or even the same user in different times, according to their mood, desire and drive. The danger with these conventional approaches is that the users tend not to develop a consistent problem-solving approach, but instead develop and utilize inefficient and undesirable study habits. Another disadvantage is that users also tend not to fully understand a question, and the reasons why one answer choice is correct, while the other answer choices are incorrect.
Existing systems and methods for work force planning and occupational re-adjustment have traditionally concentrated mainly on the manual analysis of an individual's skills, with little or no emphasis on a related job analysis or needs analysis of potential employers. Additionally, the current state of the art methods fails to link training resources and new training requirements as part of an overall approach.
There have already been proposed a certain solution in attempt to overcome these deficiencies. U.S. Pat. No. 6,157,808 disclose to an integrated system that enables developing training material, career paths or to determine an employee's qualifications, performance and comprehensive support for job and task analysis.
Another solution have been proposed by U.S. Pat. No. 5,885,087 providing a computerized learning approach that enables a user to improve their performance on multiple-choice exams. The invention forces examinees to practice their examination skills and subject matter knowledge in a systematic way.
Prior art methods, provided by a small number of tutorials, rely purely on statistical evaluation (the number of correct vs. incorrect responses). These tutorials do not, and cannot, provide any analysis regarding the reasoning behind incorrect responses, nor do they provide any kind of individually tailored program that adapts and re-adapts itself to the specialized needs of each student.
The present invention discloses a new concept for e-learning systems, which differentiate from prior art systems in the following aspects;                1. Prior art systems have no set of goals distinguishing between the student's current level and the level which is required to achieve these goals.        2. Prior art systems do not attempt to understand, diagnose and self-improve upon the reasoning behind a student's mistakes.        3. Prior art systems do not map possible reasons for each mistake, and then use a layered approach of analyzing all errors in order to formulate a diagnostic conclusion.        4. Prior art systems do not perform an on-going analysis of a student's progress throughout the learning process, identifying gaps in knowledge and skill, and then continuously updating the course level accordingly.        5. Prior art systems do not present exercises and exams on a dynamic basis, according to specific student needs diagnosed by the system.        6. Prior art systems do not rely on techniques of building a list of questions and answers, for indicating a student's weaknesses.        7. Prior art systems do not utilize the amount of time a student spent to answer a question, in order to reach conclusions on the reason why it took that amount of time to respond.        8. Prior art systems do not use hint requests to draw conclusions regarding the reasons for requesting a hint        9. Prior art systems do not match the lesson contents or the number and type of exercises with a pre-determined time frame.        10. Prior art systems do not adapt their tutorial program according to a student's likelihood of improvement in specific areas.        11. Prior art systems do not evaluate cognitive preferences in order to tailor the teaching aids used for each student.        12. Prior art systems do not save all student responses throughout the learning process, the amount of time he/she spend to complete each section, his/her responses to each question and the time taken to solve each problem.        13. Prior art systems do not structure a systematic tutorial package that guides the student automatically though a course that was designed specifically for him/her.        
The main object of the present invention is to provide an e-learning system enabling to minimize the gap between the student's current knowledge and the knowledge needed for passing a particular exam successfully or for succeeding at a specific job—and to provide the student with the tools needed to do this effectively and efficiently.
Another object of the present invention is to provide an in-depth analysis of each student's individual aptitude in 10's or even 100's of varying data elements and cognitive proficiencies.
The present invention main advantages and innovation are as follows:                1. The method in which the tutorial program is designed according to pre-evaluation of course requirements. This evaluation highlights everything required of the student in preparation for a particular exam or job position (knowledge, know-how, guiding principles, weaknesses, thought processes). The requirements and goals, which are determined for each student, are integrated into the interface of the course program, which reflects the algorithm on which the course is based.        2. The tutorial system according to the present invention collects data on the reasoning behind a students incorrect answers, and then performs a systematic analysis of the source of the student's difficulty with specific exam questions. Based on this analysis, the system then provides a tutorial program, which will guide the student through the correct method for selecting accurate responses.        3. A students proficiency is analyzed by looking, not only at which questions were answered correctly or incorrectly, but also at why a specific wrong answer was chosen over any other.        4. The system according to the present invention re-diagnoses a students level over and over at every stage, not only following final and mid-term exams presented throughout the course. The system accomplishes this goal by presenting students with various exercises throughout the program curriculum. In this way, the tutorial adjusts itself on an ongoing basis, according to a students current level at each stage of the course.        5. The lesson exercises presented to each student are selected on a dynamic basis from a large pool of questions, according to the students current level at any given stage and based on his/her performance up to that time. During an exercise or exam, the system is able to adapt questions, not only to the students level (as is common with certain tutorial software), but also according to the reasons for the particular students mistakes. The program organizes and presents the following questions accordingly—either within the same exercise or exam, or at the next exercise stage.        6. The list of possible answers for each exercise or exam question is organized in a way that each incorrect answer will point to a different error in reasoning, thus making it possible for the algorithm to analyze cognitive failures.        7. When preparing a student for an exam in which the amount of time spent on each question or section is relevant, said time is being measured. The system then analyzes the reasons why each response took a particular amount of time, and reaches relevant conclusions.        8. Certain tutorials offered by the present invention allow the student to request a ‘hint’ to the correct answer. The system analyzes and draws conclusions from the possible reasons for requesting a hint to a specific question, and from the manner wherein the hint was used (whether or not the correct response was selected).        9. When preparing a student for pre-scheduled exams, the system takes into account the time remaining before the exam (e.g. the number of weeks left multiplied by the number of hours available for study each week). The tutorial program (type and quantity of exercises and exams) will follow the allotted time frame. At the beginning of each section, the system will readjust itself according to the time remaining before the exam.        10. The student's answers as well as the amount of time it takes him/her to answer each question, will be analyzed and shall provide a basis for constantly updating the students progress. The system defines the pace of the lessons by focusing on areas where the student has the best chances to improve (time invested relative to improvement achieved).        11. Some of the present invention tutorial packages include a system that is programmed to evaluate a student's cognitive preference toward learning (audio/visual/textual) and to adapt lessons to the preferred method.        12. The present invention learning system utilizes the computer's ability to perform a multi-level analysis of a student's progress at each stage of the tutorial.        13. Based on a students performance at each level, the system is able to determine the best way to proceed in building a course of development. The student then follows through the pages, which change dynamically as the program analyzes and adapts itself to the specialized needs of the student.        